A review of CUDA optimization techniques and tools for structured grid computing

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Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

Coarse-Grain Reconfigurable Arrays (CGRAs) represent emerging low-power architectures designed to accelerate Compute-Intensive Loops (CILs). The effectiveness of CGRAs in providing acceleration relies on the quality of mapping: how efficiently the CIL is c ...

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

Logic rewriting is a powerful optimization technique that replaces small sections of a Boolean network with better implementations. Typically, exact synthesis is used to compute optimum replacement on-the-fly, with possible support for Boolean don't cares. ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

A review of CUDA optimization techniques and tools for structured grid computing

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Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

EdgeAI-Aware Design of In-Memory Computing Architectures

Secure Interface Design Leveraging Hardware/Software Support

Mesh-based topology, shape and sizing optimization of ribbed plates

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs

Scalable constrained optimization

Scalable Logic Rewriting Using Don’t Cares

Is the powersave governor really saving power?

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Accurate and agile flight with winged drones

Efficient and insightful descriptors for representing molecular and material space

Automated Formal Verification of Software Network Functions

The time-domain Cartesian multipole expansion of electromagnetic fields

A ride time-oriented scheduling algorithm for dial-a-ride problems

Highly Parallel RTL Simulation

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD